Digital single-molecule enzyme multi-activity characteristic cross-scale heterogeneity dynamic evaluation method

Abstract

The application discloses a kind of digital single molecule enzyme multi-activity characteristic cross-scale heterogeneity dynamic evaluation methods, comprising: the enzyme-template-primer ternary complex of pre-combination completion is diluted to single molecule level to be loaded into the reaction chamber in microwell array chip to carry out rolling circle amplification, and utilize molecular beacon and the fluorescence signal released by amplification product combination;Real-time monitoring and obtaining the fluorescence signal to generate time-resolved fluorescence intensity curve;The slope parameter of the fluorescence intensity curve is extracted to obtain the catalytic synthesis rate by conversion calculation for evaluating enzyme activity;The catalytic synthesis rate value distribution is fitted using n times Gaussian mixture model to obtain the standard deviation for evaluating population uniformity and the coefficient of variation for evaluating stability.The application can realize single molecule resolution, multi-parameter dynamic correlation and environmental interference processing cross-scale analysis simultaneously, and break through the resolution limit of traditional analysis technology by integrating single molecule fluorescence tracking and population statistics.

Description

Technical Field

[0001] This invention relates to the field of biomolecular detection, and in particular to a dynamic evaluation method for cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes. Background Technology

[0002] In the field of biotechnology, the catalytic performance of enzymes directly determines the efficiency and accuracy of core technologies such as DNA sequencing and biosynthesis. In particular, the development of cutting-edge platforms such as single-molecule real-time sequencing (SMRT) has placed unprecedentedly stringent demands on the catalytic rate, reaction uniformity, and environmental stability of DNA polymerases. However, current enzyme activity analysis methods have fundamental limitations; their reliance on population average measurements makes it difficult to reveal the heterogeneous characteristics of single enzyme molecules, which has become a key bottleneck restricting the rational design and screening of high-performance enzymes.

[0003] Traditional enzyme activity detection techniques, such as fluorescent substrate hydrolysis and gel electrophoresis, output average activity values ​​by measuring the collective behavior of millions to hundreds of millions of enzyme molecules. This method, based on the assumption of population homogeneity, inherently masks the significant differences in kinetic parameters among individual enzyme molecules. Within a DNA polymerase population, there may be high-rate and low-rate subpopulations, but traditional detection methods only report a statistical average. Furthermore, the differences in enzyme molecules' sensitivity to environmental disturbances, laser irradiation, and fluctuations in ion concentration are obscured; this neglect may lead to the failure to identify key performance defects. This lack of single-molecule heterogeneity makes directed evolutionary engineering less effective, potentially resulting in mutant screening that overly relies on rate enhancement while neglecting the synergistic optimization of homogeneity and stability. Ultimately, this could lead to high-rate mutants being impractical due to latent defects.

[0004] To overcome the limitations of population analysis, single-molecule detection techniques have been introduced into enzymology research, such as single-molecule fluorescence resonance energy transfer (smFRET) and optical tweezers manipulation. However, these techniques still have certain limitations. While smFRET can observe enzyme conformational changes in real time, it is difficult to simultaneously correlate catalytic rate and functional stability. Optical tweezers excel at analyzing enzyme-substrate interactions under mechanical forces but cannot simulate real reaction conditions in solution environments. Emerging nanopore sequencing platforms can obtain DNA translocation rates but struggle to distinguish between the contribution of enzyme heterogeneity and environmental noise. Furthermore, the throughput limitations and statistical requirements of these techniques are not fully compatible, and the high cost of equipment such as super-resolution microscopy and complex fluorescence labeling processes further hinder their large-scale application. Therefore, the shortcomings of existing single-molecule platforms in terms of throughput, multi-parameter integration, and environmental simulation capabilities mean that enzyme heterogeneity research remains at the observational stage, failing to establish quantifiable evaluation standards.

[0005] Therefore, developing a cross-scale analysis method that can simultaneously achieve single-molecule resolution, multi-parameter dynamic correlation, and environmental interference handling has become an urgent need to overcome the bottleneck in the development of enzyme screening and evaluation for single-molecule sequencing. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, the present invention aims to provide a method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes, which has the advantages of simultaneously achieving cross-scale analysis with single-molecule resolution, multi-parameter dynamic correlation and environmental interference treatment.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] According to embodiments of this disclosure, a method for dynamic evaluation of the cross-scale heterogeneity of multiple activity characteristics of digital single-molecule enzymes is provided, including:

[0009] The pre-bound enzyme-template-primer ternary complex was diluted to the single-molecule level and loaded into the reaction chamber of a microporous array chip for rolling circle amplification. Molecular beacons were used to bind to the amplification products and release fluorescent signals.

[0010] The fluorescence signal is monitored and acquired in real time to generate a time-resolved fluorescence intensity curve;

[0011] The slope parameter of the fluorescence intensity curve is extracted to calculate the catalytic synthesis rate through conversion, which is used to evaluate enzyme activity;

[0012] The distribution of catalytic synthesis rate values ​​was fitted using an n-fold Gaussian mixture model to obtain the standard deviation for assessing population homogeneity and the coefficient of variation for assessing stability.

[0013] In some exemplary embodiments, the microporous array chip has a size of (10-20) × (10-20) mm and has more than 10,000 reaction chambers with dimensions of (65-90) μm × (50-80) μm × (80-120) μm and a spacing of 80-120 μm. The microporous array chip is subjected to surface activation, hydrophobic coating deposition, and selective hydrophilication treatment to enhance the internal hydrophilicity and external hydrophobicity of the reaction chambers.

[0014] In some exemplary embodiments, the step of diluting the pre-bound enzyme-template-primer ternary complex to the single-molecule level for loading into the reaction chamber of a microporous array chip for rolling circle amplification specifically includes:

[0015] The target dilution factor is obtained based on the Poisson distribution formula according to the volume of the reaction chamber, so as to dilute the pre-bound enzyme-template-primer ternary complex to the predetermined concentration.

[0016] The diluted sample is loaded into a microporous array chip and distributed to each reaction chamber by capillary action or centrifugal force, so that at least some of the reaction chambers contain only one ternary complex.

[0017] The catalytic reaction is initiated to perform rolling circle amplification, and during the amplification process, the molecular beacon specifically binds to the corresponding matching sequence to release a fluorescent signal.

[0018] In some exemplary embodiments, when preparing the enzyme-template-primer ternary complex, the T4 ligase uses primers to ligate the first and last parts of the template DNA into a circular template, which serves as the substrate for the polymerase.

[0019] In some exemplary embodiments, when preparing the enzyme-template-primer ternary complex, the circular DNA template and primers are mixed in a reaction buffer at a volume ratio of 1:(2-3) for pre-hybridization, and the concentration of dNTPs is optimized to balance amplification efficiency and background noise.

[0020] In some exemplary embodiments, the reaction buffer comprises: 50 mM Tris-HCl, 10 mM MgCl2, 100 mM KCl and 1 mM dithiothreitol, the pH of the reaction buffer is maintained at 7.5-8.5, and the concentration of the dNTPs is optimized to 0.4 mM.

[0021] In some exemplary embodiments, the real-time monitoring and acquisition of the fluorescence signal to generate a time-resolved fluorescence intensity curve specifically involves:

[0022] The fluorescence intensity changes of each reaction chamber are monitored in real time by a high frame rate camera to generate raw fluorescence images for extracting fluorescence signals, and time-resolved fluorescence intensity curves are generated based on the real-time acquired fluorescence signal intensity.

[0023] In some exemplary embodiments, the step of extracting the slope parameter of the fluorescence intensity curve to calculate the catalytic synthesis rate for evaluating enzyme activity specifically includes:

[0024] After suppressing optical noise using image enhancement technology, feature hole positioning is performed based on a predefined hole location template to determine the reaction hole locations in the micro-hole array chip.

[0025] Obtain the time-series fluorescence intensity data for each reaction site and extract the slope parameter of the corresponding fluorescence intensity curve;

[0026] The catalytic synthesis rate is calculated using the calibration formula μ=k / (α·β), which is used to evaluate enzyme activity. Here, μ is the catalytic synthesis rate, k is the slope parameter, α is the background fluorescence gain coefficient, and β is the beacon binding efficiency correction factor.

[0027] In some exemplary embodiments, the step of fitting the catalytic synthesis rate value distribution using an n-fold Gaussian mixture model to obtain the standard deviation for assessing population homogeneity and the coefficient of variation for assessing stability specifically includes:

[0028] A statistical histogram is generated based on the obtained catalytic synthesis rate, and the distribution characteristics are modeled using an n-fold Gaussian function fitting method according to the modeling formula, which is:

[0029] Where n is the Gaussian multiplicity, y is the derivative of the fluorescence value, and x is the temperature sequence. The fitting function of the scipy library in Python is used to obtain the parameters that minimize the equation error.

[0030] Population homogeneity was assessed by calculating the standard deviation of the catalytic synthesis rate at 1000 reaction sites based on the obtained n-fold Gaussian mixture model.

[0031] The stability was assessed by calculating the coefficient of variation of the expected catalytic synthesis rate sequence over 900 minutes at 1-minute intervals based on the obtained n-fold Gaussian mixture model.

[0032] In some exemplary embodiments, when evaluating uniformity and stability, the enzyme synthesis rate at different concentrations is also monitored in real time to establish a double reciprocal curve, and the results are calculated according to the formula... The dynamic Michaelis constant of a single enzyme is obtained, where V0 is the reaction rate and dV is the constant. max The maximum reaction rate is given by [S], where [S] is the substrate concentration and dK is the denominator. m This is the dynamic Michaelis constant.

[0033] In some exemplary embodiments, the method further includes:

[0034] The enzyme population was irradiated with a 532 nm laser, and the formula was used to... Calculate the photodamage coefficient to quantify enzyme stability;

[0035] Constructing 50-200 mM Na + Gradient, 5-20 mM Cl - Gradient, 50-200 mM K + Gradient and 5-20 mMMg 2+ The gradient ion interference test system, through the formula Ion sensitivity index was calculated to assess the environmental sensitivity of the enzyme.

[0036] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0037] This invention provides a dynamic evaluation method for the cross-scale heterogeneity of multiple activity characteristics of digital single-molecule enzymes, enabling real-time cross-scale analysis of the multiple activity characteristics of single enzyme molecules. By integrating single-molecule fluorescence tracking and population statistics, it breaks through the resolution limitations of traditional analytical techniques, providing a dynamic and multi-dimensional evaluation tool for enzyme heterogeneity research. It can also reveal the complex trade-offs between rate, uniformity, and stability of single enzyme molecules, promoting the transformation of enzyme analysis from "static averaging" to "dynamic individualization". Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the dynamic evaluation method for cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes in an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram illustrating the basic principle of the dynamic evaluation method for cross-scale heterogeneity of multiple activity characteristics of digital single-molecule enzymes in this embodiment of the invention.

[0040] Figure 3 This is a schematic diagram illustrating the principle of the method for performing rolling circle amplification and generating fluorescence intensity curves in an embodiment of the present invention.

[0041] Figure 4 This is a schematic diagram illustrating the process of loading a ternary composite material into a microporous array chip in an embodiment of the present invention.

[0042] Figure 5 This is a diagram showing the results of verification using wild-type phi 29 DNA polymerase in an embodiment of the present invention.

[0043] Figure 6 This is a graph showing the results of evaluating the multiple activity characteristics of mutant phi 29 DNA polymerase M1 / M3 / M5 in an embodiment of the present invention.

[0044] Figure 7 This is a diagram showing the results of the multi-activity characteristics of different phi29 DNA polymerases in the embodiments of the present invention.

[0045] Figure 8 This is a diagram showing the results of evaluating the multi-activity characteristics of different phi 29 DNA polymerases after laser treatment in an embodiment of the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] like Figures 1 to 8As shown, this invention provides a method for dynamic evaluation of cross-scale heterogeneity of multiple activity characteristics of digital single-molecule enzymes (dMACE), comprising:

[0048] S100. The pre-bound enzyme-template-primer ternary complex is diluted to the single-molecule level and loaded into the reaction chamber of the microporous array chip for rolling circle amplification. Molecular beacons are used to bind to the amplification products and release fluorescent signals.

[0049] In the preparation of the enzyme-template-primer ternary complex, T4 ligase uses primers to ligate the first and second ends of the template DNA into a circular template, which serves as the substrate for polymerase. After obtaining the circular template, rolling circle amplification (RCA) is initiated for amplification. During the amplification process, deoxyribonucleotide triphosphates (dATP, dTTP, dCTP, dGTP) are used to synthesize new DNA strands. Rolling circle amplification (RCA) is an isothermal nucleic acid amplification technique based on a circular DNA template, which can generate a linear DNA product containing hundreds of repeating units after amplification.

[0050] In a specific example, when preparing the enzyme-template-primer ternary complex, a 20 μL ligation reaction system is first prepared. This system includes: T4 DNA ligase buffer, primer DNA, template DNA, nuclease-free water, and T4 DNA ligase. The initial concentration of primer DNA is 10 μM, and 2 μL is added to achieve a final concentration of 2 μM. The initial concentration of template DNA is 10 μM, and 4 μL is added to achieve a final concentration of 0.5 μM. Nuclease-free water is used to bring the total volume of the reaction system to 20 μL. Finally, 2 μL of T4 DNA ligase (400 U / μL) is added to initiate the ligation reaction.

[0051] During preparation, template DNA, primer DNA, and water are first mixed in a microcentrifuge tube according to the specified ratio. After centrifugation, the mixture is annealed at 65°C for 5 minutes. The centrifuge tube is then removed and placed in a 4°C refrigerator for 2 minutes to cool. Next, the complete ligation reaction system is prepared according to the above ratio, vortexed and centrifuged, and then reacted overnight at 16°C. In some embodiments, the reaction can also be carried out at 25°C for 2 hours or at 65°C for 10 minutes to complete the ligation reaction process.

[0052] After the ligation reaction is completed, the digestion step is performed. A digestion system containing Exo III buffer, Exo I buffer, Exo III enzyme (400 U / μL), Exo I enzyme (400 U / μL), and ddH2O (double-distilled water) needs to be prepared. After adding the digestion system to the ligation reaction product, the reaction is carried out at 37°C for 45 minutes, followed by heating at 80°C for 15 minutes to inactivate the enzyme, and finally stored at 4°C.

[0053] After the digestion step, the sample can be directly used as the stock solution or diluted 1:1 for characterization, or purified using a purification kit. The purified sample must be diluted 20-fold with dilution buffer before final characterization. Further characterization can be performed using a Thermo Fisher NanoDrop series UV spectrophotometer, fragment analyzer, or agarose gel electrophoresis.

[0054] Simultaneously, when preparing the enzyme-template-primer ternary complex, the circular DNA template and primers are mixed in the reaction buffer at a volume ratio of 1:(2-3) for pre-hybridization, and the concentration of dNTPs is optimized to balance amplification efficiency and background noise. The reaction buffer includes 50mM Tris-HCl, 10mM MgCl2, 100mM KCl, and 1mM dithiothreitol (DTT). Tris-HCl (Tris(Hydroxymethyl)Aminomethane Hydrochloride) is a commonly used biochemical buffer reagent. The pH of the reaction buffer is maintained at 7.5-8.5, and the concentration of dNTPs is optimized to 0.4mM.

[0055] In some embodiments, Tris-HCl can be replaced by HEPES (4-hydroxyethylpiperazine ethanesulfonic acid) to maintain the pH at 7.5-8.5 in order to provide the optimal pH reaction environment for the enzyme. Magnesium ions are an essential cofactor for enzyme catalytic activity, participating in the binding and hydrolysis of dNTPs (deoxynucleoside triphosphates). Adding reducing agents such as DTT can maintain enzyme stability, and protein stabilizers such as bovine serum albumin (BSA) can also be added to reduce enzyme adsorption loss and non-specific inhibition on the tube wall.

[0056] In a specific example, the reaction system was optimized by mixing circular DNA template and primers at a volume ratio of 1:2.5 in the reaction buffer for prehybridization. The reaction buffer included: 50 mM Tris-HCl, 10 mM MgCl2, 100 mM KCl, 1 mM DTT, 0.1 mg / mL BSA, and 5 μM molecular beacon. The pH of Tris-HCl was 7.5. MgCl2 was used to activate catalytic activity, KCl was used to maintain ionic strength, DTT was used to prevent enzyme oxidative inactivation, and BSA was used to reduce surface adsorption loss. The molecular beacon was designed with a stem-loop structure, with a 5 bp stem modified with a BHQ1 quencher group, a 15 nt loop that was completely complementary to the template repeat unit, and a FAM fluorescent group labeled at the 5' end. The dNTP concentration was determined to be optimal at 0.4 mM through a 0.1-1.0 mM gradient test, at which the rolling circle amplification efficiency reached its peak against the background noise. The molecular beacon was used at a concentration of 50 mM. At nM, the amplification product binding efficiency is the highest, ensuring the specificity of fluorescence signal triggering.

[0057] Understandably, when configuring the ternary complex, since the reaction system contains initiating reagents, rolling circle amplification theoretically begins at this point. The amplification reaction is continuous. Based on this, the ternary complex is diluted to the single-molecule level and then loaded into a microporous array chip for further amplification. Subsequently, the fluorescence signal intensity in the microporous array chip after amplification is used for subsequent evaluation calculations.

[0058] Specifically, S100 includes:

[0059] S101. Based on the volume of the reaction chamber and the Poisson distribution formula, obtain the target dilution factor to dilute the pre-bound enzyme-template-primer ternary complex to the predetermined concentration.

[0060] The Poisson distribution formula is λ = C * V * N, where λ represents the average number of events occurring per unit time or space, and the target value of λ is usually set to 0.1-0.2; C represents the sample concentration, in mol / L (mol / L), used to describe the density of event-prone entities (such as molecules and particles) in the system; V represents the sample volume, in L (liters), used to define the observed physical spatial range; and N represents Avogadro's constant, with a value of 6.022 × 10⁻⁶. 23 mol −1 It serves as a bridge to convert the number of moles into the absolute number of particles.

[0061] The target dilution factor is calculated using this formula. To avoid excessive errors in a single-step dilution, a multi-step dilution method is usually adopted. The diluent is preferably PBS containing BSA or other specific buffers to maintain the stability of the ternary complex and prevent its dissociation or inactivation. Each dilution step uses a high-precision pipette and a low-absorption tip, and thorough mixing is ensured to guarantee homogeneity.

[0062] S102. The diluted sample is loaded into the microporous array chip and distributed to each reaction chamber by capillary action or centrifugal force, so that at least some reaction chambers contain only one ternary complex.

[0063] The microporous array chip preferably uses a silicon-based microporous array chip fabricated by photolithography. This microporous array chip contains a large number of microporous reaction chambers to achieve high-density reaction unit integration. The reaction chambers are physically isolated from each other, and the volume of the reaction chambers can be determined by the pore size and pore depth. The diluted sample is the ternary complex dilution solution diluted to the target dilution factor. After the diluted sample is loaded into the microporous array chip, it can be distributed to each reaction chamber by capillary action or centrifugal force. Following the Poisson distribution principle in a large number of reaction chambers, most reaction chambers are microporous, some reaction chambers contain exactly one ternary complex, and a very small number of reaction chambers contain two or more ternary complexes. Since the reaction chambers are physically isolated, individual enzyme molecules can be observed independently.

[0064] The microporous array chip has a size of (10-20) × (10-20) mm and has more than 10,000 reaction chambers with dimensions of (65-90) μm × (50-80) μm × (80-120) μm and a spacing of 80-120 μm. The microporous array chip is subjected to surface activation, hydrophobic coating deposition, and selective hydrophilic treatment to enhance the hydrophilicity inside the reaction chambers and the hydrophobicity outside.

[0065] In one specific example, the microporous array chip was fabricated using a high-precision photolithography process. Specifically, a regular array with pore lengths of 82 μm, pore widths of 65 μm, pore depths of 97 μm, and pore spacing of 100 μm was constructed on a silicon substrate, achieving a high-density integration of over 10,000 reaction chambers per square centimeter. The surface of the microporous array chip was treated with oxygen plasma hydrophilization to ensure uniform filling of the reaction chambers by the reaction solution. The enzyme-template-primer ternary complex was diluted to 0.7 molecules per reaction chamber.

[0066] Furthermore, to verify the dilution effect, the proportion of fluorescence signal points observed under a microscope can be statistically determined to conform to the Poisson distribution, or the initial concentration can be deduced from the final number of fluorescence signals for evaluation and optimization.

[0067] S103 initiates the catalytic reaction to perform rolling circle amplification, and during the amplification process, the molecular beacon specifically binds to the corresponding matching sequence to release a fluorescent signal.

[0068] During rolling circle replication, the molecular beacon in the system binds specifically and complementary to the corresponding matching sequence of the DNA product. The molecular beacon has a stem-loop structure with a stem length of 5 bp and a loop length of 15 nt. Its repeating sequence targeting region is completely complementary to the repeating unit of the DNA product to ensure the specificity of signal triggering. During binding, the unfolding of the stem-loop structure of the molecular beacon causes the fluorophore and quencher groups to separate, thereby releasing a high-intensity fluorescent signal. The fluorescence intensity increases over time, and the slope of the change is proportional to the enzyme activity rate. Figure 3 As shown, Figure 3 The diagram shows the principle of the rolling circle amplification process.

[0069] S200. Real-time monitoring and acquisition of the fluorescence signal to generate a time-resolved fluorescence intensity curve. Specifically, this involves using a high frame rate camera to monitor the fluorescence intensity changes of each reaction chamber in real time and generating raw fluorescence images to extract the fluorescence signal. A time-resolved fluorescence intensity curve is then generated based on the real-time acquired fluorescence signal intensity. In practice, typically only the fluorescence signal of the positive well is detected. The positive well is the reaction chamber containing a single ternary complex, such as... Figure 4 As shown, Figure 4 A schematic diagram illustrating the changes in fluorescence signal intensity in a microporous array chip is shown.

[0070] S300. Extract the slope parameter of the fluorescence intensity curve to calculate the catalytic synthesis rate through conversion for evaluating enzyme activity.

[0071] Specifically, step S300 includes:

[0072] S301. After suppressing optical noise using image enhancement technology, feature hole positioning is performed based on a predefined hole template to determine the reaction hole positions in the micro-hole array chip.

[0073] When obtaining the original fluorescence image, an adaptive thresholding process is first used to enhance the image contrast. Then, the Canny operator is used for edge detection to extract significant edge features. Subsequently, the target region in the image is accurately located through contour search. For example, cross-correlation algorithms or machine learning segmentation models can be used for accurate location. This target region is the reaction pore, thereby eliminating interference from non-specific regions.

[0074] S302. Obtain the time-series fluorescence intensity data for each reaction well and extract the slope parameter of the corresponding fluorescence intensity curve.

[0075] After locating the reaction well sites, the next step is fluorescence signal extraction and processing. Raw fluorescence intensity data is extracted from the located well sites, and the raw fluorescence intensity data is sequentially normalized to eliminate systematic errors, baseline corrected to remove background signal interference, and smoothed using a Butterworth filter to suppress high-frequency noise. After normalization, the fluorescence intensity is mapped to the [0,1] interval to eliminate inter-well optical differences. Based on the obtained fluorescence intensity versus time relationship, a time-resolved fluorescence intensity curve can be generated. Then, by extracting the slope parameter of the fluorescence intensity curve, the instantaneous growth rate of fluorescence intensity can be calculated, capturing the dynamic characteristics of molecular binding / dissociation events.

[0076] S303. The catalytic synthesis rate is calculated by conversion according to the calibration formula μ=k / (α·β). The catalytic synthesis rate is used to evaluate enzyme activity, where μ is the catalytic synthesis rate, k is the slope parameter, α is the background fluorescence gain coefficient, and β is the beacon binding efficiency correction factor. The background fluorescence gain coefficient α and the beacon binding efficiency β are calibrated by a standard curve. The catalytic synthesis rate can be used to evaluate the absolute enzyme activity of the reaction process.

[0077] S400: The distribution of catalytic synthesis rate values ​​is fitted using an n-fold Gaussian mixture model to obtain the standard deviation for assessing population homogeneity and the coefficient of variation for assessing stability.

[0078] Specifically, step S400 includes:

[0079] S401. Based on the obtained catalytic synthesis rate, a statistical histogram is generated, and the distribution characteristics are modeled using an n-fold Gaussian function fitting method according to the modeling formula, which is:

[0080] Where n is the Gaussian multiplicity, y is the derivative of the fluorescence value, x is the temperature sequence, and the fitting function of the scipy library in Python is used to obtain the parameters that minimize the equation error, a1-a n To determine the number of samples conforming to this Gaussian distribution, σ1-σ n The standard deviation of the function is used to characterize the degree of dispersion of the sample distribution;

[0081] Where, μ1 to μ n As the mean parameter of each Gaussian component, it comprehensively characterizes the distribution characteristics of the fluorescence signal. The window size for adaptive thresholding can be adaptively adjusted according to the image resolution. The cutoff frequency and order of the Butterworth filter can be optimized according to the signal characteristics. The number of Gaussian components, n, can be determined based on the actual data distribution characteristics through model selection criteria. This implementation not only ensures the systematicness and integrity of the processing flow, but also has the advantages of strong adaptability and high configurability, realizing efficient automated processing and accurate quantitative analysis of fluorescence image data.

[0082] S402. Based on the obtained n-fold Gaussian mixture model, the standard deviation of the catalytic synthesis rate of 1000 reaction sites is calculated to evaluate the population homogeneity.

[0083] S403. Based on the obtained n-fold Gaussian mixture model, calculate the coefficient of variation of the expected value sequence of catalytic synthesis rate within 900 minutes at 1-minute intervals to evaluate stability.

[0084] Typically, the expectation-maximization algorithm can be used to optimize the eigenvalues ​​of each substate in the hybrid model. At the same time, the robustness of the model is verified by residual analysis and Bayesian information criterion during the process, providing direct evidence at the molecular mechanism level for nanoscale processes such as enzyme kinetics and protein folding.

[0085] Furthermore, in assessing uniformity and stability, the following steps are also included: S404, real-time monitoring of enzyme synthesis rates at different concentrations to establish a double reciprocal curve, and calculation according to the formula. The dynamic Michaelis constant of a single enzyme is obtained, where V0 is the reaction rate and dV is the constant. max The maximum reaction rate is given by [S], where [S] is the substrate concentration and dK is the denominator. m This is the dynamic Michaelis constant. Through the above process, dynamic monitoring can be covered from a single time point to a long time period.

[0086] Furthermore, in some embodiments, the method further includes:

[0087] S501, The enzyme population was irradiated with a 532 nm laser, and the formula was used... The photodamage coefficient is calculated to quantify enzyme stability. In the formula, γ is the photodamage coefficient, a quantitative indicator used to measure the sensitivity of enzyme molecules to photodamage. The larger the γ value, the faster the enzyme activity decays with increasing light intensity, indicating poorer photostability and greater susceptibility to photodestruction. Conversely, the smaller the γ value, the better the photostability and the more tolerant the enzyme is to light. μ represents enzyme activity, which gradually decreases with increasing light exposure time or intensity during experiments. The formula uses its natural logarithm form lnμ to more clearly reveal the kinetic characteristics of activity decay (usually conforming to first-order reaction kinetics), i.e., the relative rate of change of activity. P represents light pressure, which can be more broadly understood as the dose or intensity of light exposure. It can refer to light power density (e.g., W / cm²), light energy dose (e.g., J / cm²), or irradiation time. dP represents a small change in light intensity.

[0088] The entire derivative term d(lnμ) / dP represents the rate of change of the natural logarithm of enzyme activity with light pressure. Its value is negative because enzyme activity (μ) always decreases as light intensity (P) increases. Therefore, the negative sign (-) before the formula plays a key role: it converts this negative rate of change into a positive value, making the final calculated photodamage coefficient γ an intuitive positive number, which facilitates comparison and data analysis between different enzyme molecules or experimental conditions.

[0089] S502, constructing 50-200 mM Na + Gradient, 5-20 mM Cl - Gradient, 50-200 mM K + Gradient and 5-20mM Mg 2+ The gradient ion interference test system, through the formula Calculate the ion sensitivity index to assess the environmental sensitivity of an enzyme, where S in the formula... ion The enzyme's environmental sensitivity is represented by Δµ, where Δµ is the change in the enzyme's catalytic synthesis rate before and after a change in ion concentration, µ0 is the initial catalytic synthesis rate of the enzyme, ΔC is the change in ion concentration before and after a change in ion concentration, and C0 is the initial concentration.

[0090] The test results are output as a three-dimensional activity spectrum (μ, δ, θ) and an environmental sensitivity matrix. An increase or decrease in the standard deviation θ of the catalytic synthesis rate under different conditions indicates that fluctuations in ion concentration significantly affect the uniformity of the enzyme reaction. A negative control group was included throughout the process to ensure the validity of the data. By introducing laser irradiation and treatment with different ion concentration gradients, the effects of environmental factors on enzyme activity, efficiency, and stability can be systematically determined.

[0091] This invention provides a dynamic evaluation method for the cross-scale heterogeneity of multiple activity characteristics of digital single-molecule enzymes, enabling real-time cross-scale analysis of the multiple activity characteristics of single enzyme molecules. By integrating single-molecule fluorescence tracking and population statistics, it breaks through the resolution limitations of traditional analytical techniques, providing a dynamic and multi-dimensional evaluation tool for enzyme heterogeneity research. It can also reveal the complex trade-offs between rate, uniformity, and stability of single enzyme molecules, promoting the transformation of enzyme analysis from "static averaging" to "dynamic individualization".

[0092] This invention achieves single-molecule resolution through the physical isolation of a microporous array chip, converts enzyme activity into a quantifiable fluorescence trajectory through RCA signal amplification, and combines this with intelligent algorithms to analyze the dynamic correlation between catalytic rate, uniformity, and stability. In a typical case, dK was successfully screened using the above method. m <50 nM and δ 2The high-performance mutant with a θ value <0.25 maintains a stable θ value below 18% for continuous synthesis over 900 minutes, meeting the stringent requirements of SMRT sequencing for long-term enzyme operation. This method overcomes the limitations of traditional population averaging analysis, providing a multi-dimensional molecular-level evaluation benchmark for rational enzyme design, and is particularly suitable for screening mutant enzymes for SMRT sequencing.

[0093] Taking the analysis of functional heterogeneity of a single phi29 DNA polymerase as an example, comparative tests between wild-type and different mutants showed that, within a certain range, DNA polymerases with more suitable rates and better stability, which are more suitable for single-molecule sequencing, could be screened and evaluated. This revealed the hidden stability defect caused by the mutation. The specific test results are as follows: Figures 5 to 8 As shown:

[0094] Figure 5 The results of validation using wild-type phi 29 DNA polymerase are shown in the following figures: Figure A is a statistical distribution of the slope of the enzyme-free negative control group over time, used to calibrate the experimental group data; Figure B is a statistical distribution of the slope of the effective positive wells of the M0 single-molecule enzyme over time, where the expected value µ represents the enzyme activity rate, the standard deviation θ characterizes enzyme uniformity, and the coefficient of variation δ reflects enzyme stability; Figure C is a heatmap of the multiple activity characteristics of the M0 single-molecule enzyme; and Figure D is a distribution of the multiple activity characteristics of the M0 single-molecule enzyme.

[0095] Figure 5 The negative control group was used for calibration, which makes the performance evaluation of the M0 enzyme more accurate, and the monitoring of changes over time can better reflect the stability characteristics of the enzyme. Figure 5 The negative control group shown in Figure A (μ = 2.90, δ) 2 = 0.20, θ = 1.4) The core objective of the experiment is to quantify and calibrate the accuracy, uniformity, and stability of a method through positive and negative calibration and long-term monitoring; Figure 5 Figure B shows the wild-type M0 (μ = 4.72, δ...). 2 = 0.61, θ = 25.8), the horizontal axis of the figure represents the slope of fluorescence intensity changing with time, and the vertical axis represents the frequency of its occurrence.

[0096] Figure 6These are graphs showing the results of evaluating the multiple activity characteristics of mutant phi 29 DNA polymerases M1 / M3 / M5 in embodiments of the present invention. In Figure A, the first row shows the statistical distribution of the slope of effective positive wells for M1 single-molecule enzyme over time, where the expected value µ represents the activity rate, the standard deviation θ represents uniformity, and the coefficient of variation δ represents stability; the second row shows the statistical distribution of the slope of effective positive wells; and the third row is a scatter plot of the effective positive well slope clustering. Figure B shows the first row of the statistical distribution of the slope of effective positive wells for M3 single-molecule enzyme over time, the second row shows the statistical distribution of the effective positive well slope, and the third row is a scatter plot of the effective positive well slope clustering. Figure C shows the first row of the statistical distribution of the slope of effective positive wells for M5 single-molecule enzyme over time, and the second row shows the statistical distribution of the effective positive well slope. Figure D shows the statistical distribution of the slope of effective positive wells over time for commercial enzyme C1, with the first row being a statistical distribution of the slope of effective positive wells and the second row being a statistical distribution of the slope of effective positive wells. Figure E shows the statistical distribution of the slope of effective positive wells over time for commercial enzyme C2, with the first row being a statistical distribution of the slope of effective positive wells and the third row being a cluster scatter plot of the slope of effective positive wells. Figure F shows the statistical distribution of the slope of effective positive wells over time for commercial enzyme C3, with the first row being a statistical distribution of the slope of effective positive wells and the second row being a statistical distribution of the slope of effective positive wells.

[0097] Figure 6 The dMACE platform is used to simultaneously quantify the catalytic synthesis rate (μ, expected value of the slope distribution), uniformity (δ, standard deviation), and stability (θ, coefficient of variation of μ over time) of three mutant (M1, M3, M5) and three commercially available (C1, C2, C3) phi29 DNA polymerase variants at the single-molecule level. Each column presents three sets of analytical results for one enzyme; (ac) Characteristic description of mutant polymerases: (a) Mutant M1 (μ = 1.86, δ 2 = 0.16, θ = 10.4), (b) mutant M3 (μ = 5.58, δ = 0.16, θ = 10.4), 2 = 0.47, θ = 27.3, (c) mutant M5 (μ = 0.99, δ 2 = 0.22, θ = 12.5); (df) Characterization of commercial enzymes: (d) Commercial enzyme C1 (μ = 6.53, δ = 0.22, θ = 12.5); 2 = 0.79, θ = 21.1, (e) commercial enzyme C2 (μ = 5.07, δ 2 = 0.64, θ = 19.71, (f) Commercial enzyme C3 (μ = 0.80, δ 2 = 0.34, θ = 17.5);

[0098] For each enzyme (a to f): Top row (time-dependent distribution): The statistical distribution of the catalytic slope (k) in all positive wells changes continuously throughout the 900-minute experiment. The solid line traces the average value (μ) within each time interval. The time trajectory of the reaction; the middle row (final histogram): the frequency distribution of the final calibrated slope value (k) in all single-molecule reactions, the curve represents a Gaussian fit to the distribution, the center of which defines μ and the width (standard deviation) defines δ; the bottom row (cluster scatter plot): a scatter plot showing the slope value of each individual obtained, illustrating the dispersion and clustering of single-molecule activity, with each point representing the catalytic rate of a single enzyme molecule;

[0099] These data reveal significant differences in catalytic rate and molecular homogeneity among different enzyme variants. For example, the mutant M5 exhibits higher homogeneity (low δ) and stability (low θ) despite its slower catalytic rate, while the commercial formulation C1 has a higher catalytic rate but greater molecular heterogeneity (high δ).

[0100] Figure 7 The diagram shows the results of multiple activity characteristics of different phi29 DNA polymerases in the embodiments of the present invention. The expected value µ represents the activity rate, the standard deviation θ represents the uniformity, and the coefficient of variation δ represents the stability. In Figure A, the first row shows the statistical distribution of the effective positive slope of the C1 and M5 mixed enzyme over time; the second row shows the statistical distribution of the effective positive well slope; the third row shows a cluster scatter plot of the effective positive well slope; and the fourth row shows a violin plot of the effective positive well slope. Figure B shows the first row shows the statistical distribution of the effective positive slope of the C2 and C3 mixed enzyme over time; the second row shows the statistical distribution of the effective positive well slope; the third row shows a cluster scatter plot of the effective positive well slope; and the fourth row shows a violin plot of the effective positive well slope. Figure C shows the first row shows the statistical distribution of the effective positive slope of the M3 and M5 mixed enzyme over time; the second row shows the statistical distribution of the effective positive well slope; the third row shows a cluster scatter plot of the effective positive well slope; and the fourth row shows a violin plot of the effective positive well slope. Figure D shows the first row shows the statistical distribution of the effective positive slope of the M0 and M1 mixed enzyme over time; the second row shows the statistical distribution of the effective positive well slope; the third row shows a cluster scatter plot of the effective positive well slope; and the fourth row shows a violin plot of the effective positive well slope.

[0101] Figure 7 In this study, dMACE was used to analyze subpopulations in mixed enzyme samples. The dMACE platform was used to analyze the multi-activity characteristics of heterogeneous mixtures containing two different phi29 DNA polymerase variants in each sample. This method successfully identified and quantified the constituent enzyme subpopulations based on their different catalytic characteristics.

[0102] For each mixture (ad), the analysis is performed from four perspectives: Top row (slope distribution over time): The evolution of the slope (k) distribution in all active single enzyme microwells during the 900-minute experiment. The bimodal distribution indicates the existence of two enzyme groups with different catalytic synthesis rates (μ1 and μ2); Second row (final slope histogram): The frequency distribution of the final slope values ​​at the end of the experiment. The solid line represents the Gaussian fit for each subgroup, from which the average catalytic rate (μ, peak center) and uniformity (δ, standard deviation of the fit) can be obtained; Third row (cluster scatter plot): A scatter plot of the slope values ​​for each individual, clearly showing that the data points cluster into two different groups, corresponding to the two enzyme variants in the mixture; Bottom row (violin plot): Shows the distribution (shape) of the slope values ​​in the population, the statistical quartiles (internal box plot), and the median (white dot); This plot highlights the differences in density and distribution between the two subpopulations.

[0103] Figure 8 These are graphs showing the results of evaluating the multi-activity characteristics of different phi 29 DNA polymerases after laser treatment in this embodiment of the invention. The expected value µ represents the activity rate, the standard deviation θ represents uniformity, and the coefficient of variation δ represents stability. Specifically, Figure A is a schematic diagram of enzyme activity distribution after laser treatment; Figure B shows the first row as a heatmap of the multi-activity characteristics of C1 single-molecule enzyme before laser treatment, and the second row as a heatmap of the multi-activity characteristics of C1 single-molecule enzyme after laser treatment; Figure C shows the first row as a heatmap of the multi-activity characteristics of C2 single-molecule enzyme before laser treatment, and the second row as a heatmap of the multi-activity characteristics of C2 single-molecule enzyme after laser treatment; Figure D shows the first row as a heatmap of the multi-activity characteristics of C3 single-molecule enzyme before laser treatment, and the second row as a heatmap of the multi-activity characteristics of C3 single-molecule enzyme after laser treatment; Figure E shows the first row as a heatmap of the multi-activity characteristics of M0 single-molecule enzyme before laser treatment; and Figure E shows the first row as a heatmap of the multi-activity characteristics of M0 single-molecule enzyme before laser treatment. Figure F shows the heatmap of multiple activities of a single enzyme, with the second row showing the heatmap of multiple activities of M0 single enzyme after laser treatment; Figure G shows the heatmap of multiple activities of M3 single enzyme before laser treatment, with the second row showing the heatmap of M3 single enzyme after laser treatment; Figure H shows the heatmap of multiple activities of M5 single enzyme before laser treatment, with the second row showing the heatmap of M5 single enzyme after laser treatment.

[0104] Figure 8 The effects of quantitative laser induction on the multi-activity characteristics of phi29 DNA polymerase were investigated. Enzyme samples from six polymerase variants (commercial: C1, C2, C3; wild-type: M0; mutant: M1, M3, M5) were irradiated with a 30 mW laser for 30 minutes. Their functional parameters were then evaluated in real time using the dMACE platform, and the multi-activity profile was quantitatively analyzed to assess photostability, a key indicator in SMRT sequencing applications.

[0105] (a) The enzyme complex is first treated with laser, and then encapsulated and monitored in real time on the dMACE platform to quantify the changes in catalytic performance; (bh) Multi-faceted analysis of each polymerase variant before and after laser irradiation, top row (heatmap): a two-dimensional density map of catalytic slope (k, x-axis) versus observation time (time interval, y-axis), with color intensity corresponding to the number of individual enzyme molecules exhibiting a specific slope at a given time, visually demonstrating the dynamic activity distribution and its evolution.

[0106] The quantized multi-activity parameters after laser processing are: (b) C1: μ = 4.37, δ 2 = 1.35, θ = 30.8; (c) C2: μ = 3.79, δ 2 = 0.76, θ = 26.4; (d) C3: μ = 0.78, δ 2 = 0.39, θ = 21.3; (e) M0: μ = 3.43, δ 2 = 1.02, θ = 43.1; (f) M1: μ = 1.44, δ 2 = 0.23, θ = 26.5; (g) M3: μ = 4.21, δ 2 = 0.84, θ = 63.7; (h) M5: μ = 0.82, δ 2 = 0.26, θ = 20.7;

[0107] These data clearly demonstrate that laser irradiation leads to a specific reduction in enzyme activity and a distinct pattern of functional degradation. The mutant M5 exhibits excellent photostability and has the lowest coefficient of variation (θ = 20.7), indicating minimal loss of activity consistency over time, which is an ideal characteristic for long-read sequencing applications.

[0108] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention. These are all equivalent modifications and improvements made to the above embodiments based on the essential technology of the present invention, and all of these fall within the protection scope of the present invention.

Claims

1. A method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes, characterized in that, include: The pre-bound enzyme-template-primer ternary complex was diluted to the single-molecule level and loaded into the reaction chamber of a microporous array chip for rolling circle amplification. Molecular beacons were used to bind to the amplification products and release fluorescent signals. The fluorescence signal is monitored and acquired in real time to generate a time-resolved fluorescence intensity curve; The slope parameter of the fluorescence intensity curve is extracted to calculate the catalytic synthesis rate through conversion, which is used to evaluate enzyme activity; The distribution of catalytic synthesis rate values ​​was fitted using an n-fold Gaussian mixture model to obtain the standard deviation for assessing population homogeneity and the coefficient of variation for assessing stability. Specifically, the step of extracting the slope parameter of the fluorescence intensity curve to calculate the catalytic synthesis rate for evaluating enzyme activity includes: After suppressing optical noise using image enhancement technology, feature hole positioning is performed based on a predefined hole location template to determine the reaction hole locations in the micro-hole array chip. Obtain the time-series fluorescence intensity data for each reaction site and extract the slope parameter of the corresponding fluorescence intensity curve; The catalytic synthesis rate is calculated by conversion according to the calibration formula μ=k / (α·β), and the catalytic synthesis rate is used to evaluate enzyme activity, where μ is the catalytic synthesis rate, k is the slope parameter, α is the background fluorescence gain coefficient, and β is the beacon binding efficiency correction factor. The specific steps of fitting the catalytic synthesis rate distribution using an n-fold Gaussian mixture model to obtain the standard deviation for assessing population homogeneity and the coefficient of variation for assessing stability include: A statistical histogram is generated based on the obtained catalytic synthesis rate, and the distribution characteristics are modeled using an n-fold Gaussian function fitting method according to the modeling formula, which is: Where n is the Gaussian multiplicity, y is the derivative of the fluorescence value, and x is the temperature sequence. The fitting function of the scipy library in Python is used to obtain the parameters that minimize the equation error. Population homogeneity was assessed by calculating the standard deviation of the catalytic synthesis rate at 1000 reaction sites based on the obtained n-fold Gaussian mixture model. The stability was assessed by calculating the coefficient of variation of the expected catalytic synthesis rate sequence over 900 minutes at 1-minute intervals based on the obtained n-fold Gaussian mixture model.

2. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, The microporous array chip has a size of (10-20) × (10-20) mm and has more than 10,000 reaction chambers. The reaction chambers have a size of (65-90) μm × (50-80) μm × (80-120) μm and a spacing of 80-120 μm. The microporous array chip is subjected to surface activation, hydrophobic coating deposition, and selective hydrophilication treatment to enhance the hydrophilicity inside the reaction chambers and the hydrophobicity outside.

3. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, The pre-bound enzyme-template-primer ternary complex is diluted to a single-molecule level and loaded into the reaction chamber of a microwell array chip for rolling circle amplification. This process specifically includes: The target dilution factor is obtained based on the Poisson distribution formula according to the volume of the reaction chamber, so as to dilute the pre-bound enzyme-template-primer ternary complex to the predetermined concentration. The diluted sample is loaded into a microporous array chip and distributed to each reaction chamber by capillary action or centrifugal force, so that at least some of the reaction chambers contain only one ternary complex. The catalytic reaction is initiated to perform rolling circle amplification, and during the amplification process, the molecular beacon specifically binds to the corresponding matching sequence to release a fluorescent signal.

4. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, When preparing the enzyme-template-primer ternary complex, T4 ligase uses primers to ligate the first and last parts of the template DNA into a circular template, which serves as the substrate for the polymerase.

5. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, 2, or 3, characterized in that, When preparing the enzyme-template-primer ternary complex, the circular DNA template and primers are mixed in the reaction buffer at a volume ratio of 1:(2-3) for pre-hybridization, and the concentration of dNTPs is optimized to balance amplification efficiency and background noise.

6. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 5, characterized in that, The reaction buffer comprises 50 mM Tris-HCl, 10 mM MgCl2, 100 mM KCl, and 1 mM dithiothreitol. The pH of the reaction buffer is maintained at 7.5-8.5, and the concentration of the dNTPs is optimized to 0.4 mM.

7. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, The real-time monitoring and acquisition of the fluorescence signal to generate a time-resolved fluorescence intensity curve specifically involves: The fluorescence intensity changes of each reaction chamber are monitored in real time by a high frame rate camera to generate raw fluorescence images for extracting fluorescence signals, and time-resolved fluorescence intensity curves are generated based on the real-time acquired fluorescence signal intensity.

8. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, To assess homogeneity and stability, the enzyme synthesis rate at different concentrations was monitored in real time to establish a double reciprocal curve, and the results were analyzed according to the formula... The dynamic Michaelis constant of a single enzyme is obtained, where V0 is the reaction rate and dV is the constant. max The maximum reaction rate is given by [S], where [S] is the substrate concentration and dK is the denominator. m This is the dynamic Michaelis constant.

9. The method for dynamic evaluation of cross-scale heterogeneity of multi-activity characteristics of digital single-molecule enzymes according to claim 1, characterized in that, The method further includes: The enzyme population was irradiated with a 532 nm laser, and the formula was used to... Calculate the photodamage coefficient to quantify enzyme stability; Constructing 50-200 mM Na + Gradient, 5-20 mM Cl - Gradient, 50-200 mM K + Gradient and 5-20 mM Mg 2+ The gradient ion interference test system, through the formula Ion sensitivity index was calculated to assess the environmental sensitivity of the enzyme.

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